164 citations · 370 across the 24 of their papers we have counts for
3 papers · 1 filter
CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance
Andrew Jesson, Nicolas Guizard, Sina Hamidi Ghalehjegh +3
We introduce CASED, a novel curriculum sampling algorithm that facilitates the optimization of deep learning segmentation or detection models on data sets with extreme class imbala…
Adversarially Learned Mixture Model
Andrew Jesson, Cécile Low-Kam, Tanya Nair +3
The Adversarially Learned Mixture Model (AMM) is a generative model for unsupervised or semi-supervised data clustering. The AMM is the first adversarially optimized method to mode…
On the Importance of Attention in Meta-Learning for Few-Shot Text Classification
Xiang Jiang, Mohammad Havaei, Gabriel Chartrand +5
Current deep learning based text classification methods are limited by their ability to achieve fast learning and generalization when the data is scarce. We address this problem by…